default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDIvor W. Tsang
Ivor Wai-Hung Tsang
Person information
- affiliation: A*STAR, Singapore
- affiliation: University of Technology Sydney, Australia
- affiliation (2008 - 2014): Nanyang Technological University, Singapore
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j154]Feiyang Ye
, Baijiong Lin, Zhixiong Yue, Yu Zhang, Ivor W. Tsang:
Multi-objective meta-learning. Artif. Intell. 335: 104184 (2024)- [j153]Xingrui Yu, Bo Han, Ivor W. Tsang:
USN: A Robust Imitation Learning Method against Diverse Action Noise. J. Artif. Intell. Res. 79: 1237-1280 (2024) - [j152]Bowen Xing, Ivor W. Tsang:
Exploiting Contextual Target Attributes for Target Sentiment Classification. J. Artif. Intell. Res. 80: 419-439 (2024) - [j151]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Generative Adversarial Ranking Nets. J. Mach. Learn. Res. 25: 119:1-119:35 (2024) - [j150]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Sanitized clustering against confounding bias. Mach. Learn. 113(6): 3711-3730 (2024) - [j149]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
PROUD: PaRetO-gUided diffusion model for multi-objective generation. Mach. Learn. 113(9): 6511-6538 (2024) - [j148]Bowen Xing, Ivor W. Tsang:
Co-Guiding for Multi-Intent Spoken Language Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 2965-2980 (2024) - [j147]Xu Chen, Yuangang Pan, Ivor W. Tsang, Ya Zhang:
Learning node representations against perturbations. Pattern Recognit. 145: 109976 (2024) - [j146]Yu Wang, Liang Hu, Xiaofeng Cao, Yi Chang, Ivor W. Tsang:
Enhancing Locally Adaptive Smoothing of Graph Neural Networks Via Laplacian Node Disagreement. IEEE Trans. Knowl. Data Eng. 36(3): 1099-1112 (2024) - [j145]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Differential-Critic GAN: Generating What You Want by a Cue of Preferences. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3754-3768 (2024) - [j144]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection. IEEE Trans. Neural Networks Learn. Syst. 35(3): 4206-4219 (2024) - [j143]Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao:
Coarse-to-Fine Contrastive Learning on Graphs. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4622-4634 (2024) - [j142]Maosen Li, Siheng Chen, Yanning Shen, Genjia Liu, Ivor W. Tsang, Ya Zhang:
Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4768-4782 (2024) - [j141]Defu Liu, Ivor W. Tsang, Guowu Yang:
A Convergence Path to Deep Learning on Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5170-5182 (2024) - [j140]Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor W. Tsang, Fang Chen:
Imitation Learning: Progress, Taxonomies and Challenges. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6322-6337 (2024) - [j139]Xiaofeng Cao, Ivor W. Tsang:
Distribution Matching for Machine Teaching. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12316-12329 (2024) - [c146]Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang:
Multisize Dataset Condensation. ICLR 2024 - [c145]Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor W. Tsang, Ya Zhang, Yanfeng Wang:
On Harmonizing Implicit Subpopulations. ICLR 2024 - [c144]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. ICLR 2024 - [c143]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. ICLR 2024 - [c142]Cheng Chen, Ivor W. Tsang:
Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision. Tiny Papers @ ICLR 2024 - [c141]Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor W. Tsang:
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning. ICLR 2024 - [c140]Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang:
Diversified Batch Selection for Training Acceleration. ICML 2024 - [c139]Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods. ICML 2024 - [c138]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. ICML 2024 - [c137]Yilong Wang, Haishan Ye, Guang Dai, Ivor W. Tsang:
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? ICML 2024 - [c136]Kairui Hu, Ming Yan, Wen Haw Chong, Yong Keong Yap, Cuntai Guan, Joey Tianyi Zhou, Ivor W. Tsang:
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. IJCNN 2024: 1-8 - [c135]Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang:
Cross-Context Backdoor Attacks against Graph Prompt Learning. KDD 2024: 2094-2105 - [c134]Cheng Chen, Bowen Xing, Ivor W. Tsang:
Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding. ECML/PKDD (4) 2024: 107-125 - [i123]Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang:
A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. CoRR abs/2401.09257 (2024) - [i122]Jinliang Deng, Xuan Song, Ivor W. Tsang, Hui Xiong:
The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting. CoRR abs/2401.11929 (2024) - [i121]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (2024) - [i120]Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor W. Tsang:
Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. CoRR abs/2402.15173 (2024) - [i119]Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang:
Multisize Dataset Condensation. CoRR abs/2403.06075 (2024) - [i118]Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor W. Tsang, Qing Guo:
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial Trajectory. CoRR abs/2403.12445 (2024) - [i117]Ming Yan, Joey Tianyi Zhou, Ivor W. Tsang:
Collaborative Knowledge Infusion for Low-resource Stance Detection. CoRR abs/2403.19219 (2024) - [i116]Bowen Xing, Ivor W. Tsang:
HC2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding. CoRR abs/2405.06204 (2024) - [i115]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. CoRR abs/2405.17761 (2024) - [i114]Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang:
Cross-Context Backdoor Attacks against Graph Prompt Learning. CoRR abs/2405.17984 (2024) - [i113]Yueming Lyu, Kim Yong Tan, Yew Soon Ong, Ivor W. Tsang:
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation. CoRR abs/2406.00812 (2024) - [i112]Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang:
Diversified Batch Selection for Training Acceleration. CoRR abs/2406.04872 (2024) - [i111]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
PROUD: PaRetO-gUided Diffusion Model for Multi-objective Generation. CoRR abs/2407.04493 (2024) - 2023
- [j138]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
LADDER: Latent boundary-guided adversarial training. Mach. Learn. 112(10): 3851-3879 (2023) - [j137]Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang:
Latent Class-Conditional Noise Model. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 9964-9980 (2023) - [j136]Yongshun Gong, Zhibin Li, Wei Liu, Xiankai Lu, Xinwang Liu, Ivor W. Tsang, Yilong Yin:
Missingness-Pattern-Adaptive Learning With Incomplete Data. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 11053-11066 (2023) - [j135]Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang:
Earning Extra Performance From Restrictive Feedbacks. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11753-11765 (2023) - [j134]Bowen Xing, Ivor W. Tsang:
Relational Temporal Graph Reasoning for Dual-Task Dialogue Language Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13170-13184 (2023) - [j133]Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang:
Data-Efficient Learning via Minimizing Hyperspherical Energy. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13422-13437 (2023) - [j132]Defu Liu, Wen Li, Lixin Duan, Ivor W. Tsang, Guowu Yang:
Noisy Label Learning With Provable Consistency for a Wider Family of Losses. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13536-13552 (2023) - [j131]Bing Li, Wei Cui, Le Zhang, Ce Zhu, Wei Wang, Ivor W. Tsang, Joey Tianyi Zhou:
DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13586-13598 (2023) - [j130]Yuhao Liu, Qing Guo, Lan Fu, Zhanghan Ke, Ke Xu, Wei Feng, Ivor W. Tsang, Rynson W. H. Lau:
Structure-Informed Shadow Removal Networks. IEEE Trans. Image Process. 32: 5823-5836 (2023) - [j129]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Latent Representation Guided Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7082-7087 (2023) - [j128]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 35(8): 7665-7680 (2023) - [j127]Hui Xu, Changyu Li, Yan Zhang, Lixin Duan, Ivor W. Tsang, Jie Shao:
MetaCAR: Cross-Domain Meta-Augmentation for Content-Aware Recommendation. IEEE Trans. Knowl. Data Eng. 35(8): 8199-8212 (2023) - [j126]Shudong Huang, Yixi Liu, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity. IEEE Trans. Knowl. Data Eng. 35(8): 8270-8281 (2023) - [j125]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Attraction and Contrastive Repulsion for Representation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j124]Yiming Xu, Lin Chen, Lixin Duan, Ivor W. Tsang, Jiebo Luo:
Open Set Domain Adaptation With Soft Unknown-Class Rejection. IEEE Trans. Neural Networks Learn. Syst. 34(3): 1601-1612 (2023) - [j123]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan, Jingchao Su:
Toward Equivalent Transformation of User Preferences in Cross Domain Recommendation. ACM Trans. Inf. Syst. 41(1): 14:1-14:31 (2023) - [c133]Haotian Wu, Bowen Xing, Ivor W. Tsang:
MTKDN: Multi-Task Knowledge Disentanglement Network for Recommendation. CIKM 2023: 4360-4364 - [c132]Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Liang Hu, Ivor W. Tsang:
Causal Intervention for Abstractive Related Work Generation. EMNLP (Findings) 2023: 2148-2159 - [c131]Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor W. Tsang, Song Wang:
Leveraging Inpainting for Single-Image Shadow Removal. ICCV 2023: 13009-13018 - [c130]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Iterative Machine Teaching. ICML 2023: 40851-40870 - [c129]Feiyang Ye, Xuehao Wang, Yu Zhang, Ivor W. Tsang:
Multi-Task Learning via Time-Aware Neural ODE. IJCAI 2023: 4495-4503 - [c128]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. NeurIPS 2023 - [c127]Bowen Xing, Ivor W. Tsang:
Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. ECML/PKDD (1) 2023: 305-322 - [i110]Yuhao Liu, Qing Guo, Lan Fu, Zhanghan Ke, Ke Xu, Wei Feng, Ivor W. Tsang, Rynson W. H. Lau:
Structure-Informed Shadow Removal Networks. CoRR abs/2301.03182 (2023) - [i109]Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor W. Tsang, Song Wang:
Leveraging Inpainting for Single-Image Shadow Removal. CoRR abs/2302.05361 (2023) - [i108]Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang:
Latent Class-Conditional Noise Model. CoRR abs/2302.09595 (2023) - [i107]Cheng Chen, Yueming Lyu, Ivor W. Tsang:
Adversary-Aware Partial label learning with Label distillation. CoRR abs/2304.00498 (2023) - [i106]Kim Yong Tan, Yueming Lyu, Yew Soon Ong, Ivor W. Tsang:
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search. CoRR abs/2304.02350 (2023) - [i105]Yaxin Shi, Xiaowei Zhou, Ping Liu, Ivor W. Tsang:
UTSGAN: Unseen Transition Suss GAN for Transition-Aware Image-to-image Translation. CoRR abs/2304.11955 (2023) - [i104]Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang:
Earning Extra Performance from Restrictive Feedbacks. CoRR abs/2304.14831 (2023) - [i103]Xiaoguang Li, Qing Guo, Pingping Cai, Wei Feng, Ivor W. Tsang, Song Wang:
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal. CoRR abs/2305.10640 (2023) - [i102]Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, Ivor W. Tsang:
Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting. CoRR abs/2305.13036 (2023) - [i101]Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Ivor W. Tsang:
Causal Intervention for Abstractive Related Work Generation. CoRR abs/2305.13685 (2023) - [i100]Yihao Huang, Yue Cao, Tianlin Li, Felix Juefei-Xu, Di Lin, Ivor W. Tsang, Yang Liu, Qing Guo:
On the Robustness of Segment Anything. CoRR abs/2305.16220 (2023) - [i99]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Iterative Machine Teaching. CoRR abs/2306.03007 (2023) - [i98]Bowen Xing, Ivor W. Tsang:
Co-evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. CoRR abs/2306.04340 (2023) - [i97]Bowen Xing, Ivor W. Tsang:
Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding. CoRR abs/2306.09114 (2023) - [i96]Canyu Zhang, Qing Guo, Xiaoguang Li, Renjie Wan, Hongkai Yu, Ivor W. Tsang, Song Wang:
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting. CoRR abs/2307.14489 (2023) - [i95]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. CoRR abs/2308.10547 (2023) - [i94]Kairui Hu, Ming Yan, Joey Tianyi Zhou, Ivor W. Tsang, Wen Haw Chong, Yong Keong Yap:
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. CoRR abs/2308.16763 (2023) - [i93]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. CoRR abs/2310.11890 (2023) - [i92]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Sanitized Clustering against Confounding Bias. CoRR abs/2311.01252 (2023) - [i91]Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang, James T. Kwok:
Aggregation Weighting of Federated Learning via Generalization Bound Estimation. CoRR abs/2311.05936 (2023) - [i90]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. CoRR abs/2311.10318 (2023) - [i89]Bowen Xing, Ivor W. Tsang:
Co-guiding for Multi-intent Spoken Language Understanding. CoRR abs/2312.03716 (2023) - [i88]Bowen Xing, Ivor W. Tsang:
Exploiting Contextual Target Attributes for Target Sentiment Classification. CoRR abs/2312.13766 (2023) - [i87]Tuan-Anh Vu, Duc Thanh Nguyen, Qing Guo, Binh-Son Hua, Nhat Minh Chung, Ivor W. Tsang, Sai-Kit Yeung:
Leveraging Open-Vocabulary Diffusion to Camouflaged Instance Segmentation. CoRR abs/2312.17505 (2023) - 2022
- [j122]Bowen Xing, Ivor W. Tsang:
Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis. J. Artif. Intell. Res. 74: 627-659 (2022) - [j121]Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, Joey Tianyi Zhou:
XAI Beyond Classification: Interpretable Neural Clustering. J. Mach. Learn. Res. 23: 6:1-6:28 (2022) - [j120]Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama:
Fast and Robust Rank Aggregation against Model Misspecification. J. Mach. Learn. Res. 23: 23:1-23:35 (2022) - [j119]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Multiple partitions alignment via spectral rotation. Mach. Learn. 111(3): 1049-1072 (2022) - [j118]Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya Zhang, Ivor W. Tsang:
Learning on Attribute-Missing Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 740-757 (2022) - [j117]Yang Zhang, Ivor W. Tsang, Yawei Luo, Changhui Hu, Xiaobo Lu, Xin Yu:
Recursive Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 4321-4338 (2022) - [j116]Xiaofeng Cao, Ivor W. Tsang:
Distribution Disagreement via Lorentzian Focal Representation. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6872-6889 (2022) - [j115]Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7955-7974 (2022) - [j114]Shudong Huang, Wei Shi, Zenglin Xu, Ivor W. Tsang, Jiancheng Lv:
Efficient federated multi-view learning. Pattern Recognit. 131: 108817 (2022) - [j113]Xiaofeng Cao, Ivor W. Tsang, Jianliang Xu:
Cold-Start Active Sampling Via γ-Tube. IEEE Trans. Cybern. 52(7): 6034-6045 (2022) - [j112]Bowen Xing, Ivor W. Tsang:
Understand Me, if You Refer to Aspect Knowledge: Knowledge-Aware Gated Recurrent Memory Network. IEEE Trans. Emerg. Top. Comput. Intell. 6(5): 1092-1102 (2022) - [j111]Liang Feng, Yuxiao Huang, Ivor W. Tsang, Abhishek Gupta, Ke Tang, Kay Chen Tan, Yew-Soon Ong:
Towards Faster Vehicle Routing by Transferring Knowledge From Customer Representation. IEEE Trans. Intell. Transp. Syst. 23(2): 952-965 (2022) - [j110]Yan Zhang, Ivor W. Tsang, Hongzhi Yin, Guowu Yang, Defu Lian, Jingjing Li:
Deep Pairwise Hashing for Cold-Start Recommendation. IEEE Trans. Knowl. Data Eng. 34(7): 3169-3181 (2022) - [j109]Huiting Hong, Xin Li, Yuangang Pan, Ivor W. Tsang:
Domain-Adversarial Network Alignment. IEEE Trans. Knowl. Data Eng. 34(7): 3211-3224 (2022) - [j108]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 34(12): 5869-5883 (2022) - [j107]Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor W. Tsang:
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j106]Xiaobo Shen, Guohua Dong, Yuhui Zheng, Long Lan, Ivor W. Tsang, Quan-Sen Sun:
Deep Co-Image-Label Hashing for Multi-Label Image Retrieval. IEEE Trans. Multim. 24: 1116-1126 (2022) - [j105]Xiaofeng Cao, Ivor W. Tsang:
Shattering Distribution for Active Learning. IEEE Trans. Neural Networks Learn. Syst. 33(1): 215-228 (2022) - [j104]Jing Chai, Ivor W. Tsang:
Learning With Label Proportions by Incorporating Unmarked Data. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5898-5912 (2022) - [c126]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu:
Multi-View Clustering on Topological Manifold. AAAI 2022: 6944-6951 - [c125]Bowen Xing, Ivor W. Tsang:
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. ACL (Findings) 2022: 3611-3621 - [c124]Bowen Xing, Ivor W. Tsang:
Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. EMNLP 2022: 159-169 - [c123]Bowen Xing, Ivor W. Tsang:
Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. EMNLP 2022: 3964-3975 - [c122]Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao:
Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. ICDE 2022: 2942-2955 - [c121]Bowen Xing, Ivor W. Tsang:
Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning. IJCAI 2022: 4425-4431 - [c120]Shudong Huang, Yixi Liu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Learning Smooth Representation for Multi-view Subspace Clustering. ACM Multimedia 2022: 3421-3429 - [c119]Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv:
Multi-view Subspace Clustering on Topological Manifold. NeurIPS 2022 - [c118]Xiaowei Zhou, Jie Yin, Ivor W. Tsang:
Edge but not Least: Cross-View Graph Pooling. ECML/PKDD (2) 2022: 344-359 - [e2]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India. Proceedings of Machine Learning Research 189, PMLR 2022 [contents] - [i86]Bowen Xing, Ivor W. Tsang:
DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification. CoRR abs/2201.00989 (2022) - [i85]Bowen Xing, Ivor W. Tsang:
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. CoRR abs/2203.03856 (2022) - [i84]Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao:
Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. CoRR abs/2204.00327 (2022) - [i83]Bowen Xing, Ivor W. Tsang:
Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning. CoRR abs/2205.10970 (2022) - [i82]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
Latent Boundary-guided Adversarial Training. CoRR abs/2206.03717 (2022) - [i81]Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang:
Data-Efficient Learning via Minimizing Hyperspherical Energy. CoRR abs/2206.15204 (2022) - [i80]Xiaofeng Cao, Yaming Guo, Tieru Wu, Ivor W. Tsang:
When an Active Learner Meets a Black-box Teacher. CoRR abs/2206.15205 (2022) - [i79]Xiaofeng Cao, Weixin Bu, Shengjun Huang, Ying-Peng Tang, Yaming Guo, Yi Chang, Ivor W. Tsang:
A Survey of Learning on Small Data. CoRR abs/2207.14443 (2022) - [i78]Bowen Xing, Ivor W. Tsang:
Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. CoRR abs/2210.10369 (2022) - [i77]Bowen Xing, Ivor W. Tsang:
Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. CoRR abs/2210.10375 (2022) - [i76]Chen Zhang, Xiaofeng Cao, Yi Chang, Ivor W. Tsang:
One-shot Machine Teaching: Cost Very Few Examples to Converge Faster. CoRR abs/2212.06416 (2022) - [i75]Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao:
Coarse-to-Fine Contrastive Learning on Graphs. CoRR abs/2212.06423 (2022) - 2021
- [j103]Yuangang Pan, Ivor W. Tsang, Yueming Lyu, Avinash Kumar Singh, Chin-Teng Lin:
Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation. Neural Comput. 33(6): 1616-1655 (2021) - [j102]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Complementary Attributes: A New Clue to Zero-Shot Learning. IEEE Trans. Cybern. 51(3): 1519-1530 (2021) - [j101]Yang Zhang, Ivor W. Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu:
Face Hallucination With Finishing Touches. IEEE Trans. Image Process. 30: 1728-1743 (2021) - [j100]Jinliang Deng, Xiusi Chen, Zipei Fan, Renhe Jiang, Xuan Song, Ivor W. Tsang:
The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting. ACM Trans. Knowl. Discov. Data 15(6): 103:1-103:25 (2021) - [j99]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-Preserving Stochastic Gradual Learning. IEEE Trans. Knowl. Data Eng. 33(8): 3129-3140 (2021) - [c117]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. KDD 2021: 269-278 - [c116]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu:
CDD: Multi-view Subspace Clustering via Cross-view Diversity Detection. ACM Multimedia 2021: 2308-2316 - [c115]Xiaowei Zhou, Jie Yin, Ivor W. Tsang, Chen Wang:
Human-Understandable Decision Making for Visual Recognition. PAKDD (3) 2021: 168-180 - [c114]Yueming Lyu, Ivor W. Tsang:
Black-Box Optimizer with Stochastic Implicit Natural Gradient. ECML/PKDD (3) 2021: 217-232 - [e1]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Proceedings of Machine Learning Research 157, PMLR 2021 [contents] - [i74]Xiaowei Zhou, Jie Yin, Ivor W. Tsang, Chen Wang:
Human-Understandable Decision Making for Visual Recognition. CoRR abs/2103.03429 (2021) - [i73]Yaxin Shi, Xiaowei Zhou, Ping Liu, Ivor W. Tsang:
Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation. CoRR abs/2103.05193 (2021) - [i72]Xiaofeng Cao, Ivor W. Tsang:
Bayesian Active Learning by Disagreements: A Geometric Perspective. CoRR abs/2105.02543 (2021) - [i71]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Conditional Transport for Representation Learning. CoRR abs/2105.03746 (2021) - [i70]Xiaofeng Cao, Ivor W. Tsang:
Distribution Matching for Machine Teaching. CoRR abs/2105.13809 (2021) - [i69]Yueming Lyu, Ivor W. Tsang:
Neural Optimization Kernel: Towards Robust Deep Learning. CoRR abs/2106.06097 (2021) - [i68]Bowen Xing, Ivor W. Tsang:
Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis. CoRR abs/2106.10816 (2021) - [i67]Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor W. Tsang, Fang Chen:
Imitation Learning: Progress, Taxonomies and Opportunities. CoRR abs/2106.12177 (2021) - [i66]Maosen Li, Siheng Chen, Yanning Shen, Genjia Liu, Ivor W. Tsang, Ya Zhang:
Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network. CoRR abs/2107.00894 (2021) - [i65]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Differential-Critic GAN: Generating What You Want by a Cue of Preferences. CoRR abs/2107.06700 (2021) - [i64]Bowen Xing, Ivor W. Tsang:
Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network. CoRR abs/2108.02352 (2021) - [i63]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting. CoRR abs/2109.01657 (2021) - [i62]Xiaowei Zhou, Jie Yin, Ivor W. Tsang:
Edge but not Least: Cross-View Graph Pooling. CoRR abs/2109.11796 (2021) - [i61]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
TRIP: Refining Image-to-Image Translation via Rival Preferences. CoRR abs/2111.13411 (2021) - [i60]Jing Li, Yuangang Pan, Ivor W. Tsang:
Taming Overconfident Prediction on Unlabeled Data from Hindsight. CoRR abs/2112.08200 (2021) - 2020
- [j98]Yan Zhang, Ivor W. Tsang, Lixin Duan:
Collaborative Generative Hashing for Marketing and Fast Cold-Start Recommendation. IEEE Intell. Syst. 35(5): 84-95 (2020) - [j97]Shudong Huang, Zenglin Xu, Ivor W. Tsang, Zhao Kang:
Auto-weighted multi-view co-clustering with bipartite graphs. Inf. Sci. 512: 18-30 (2020) - [j96]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Improving Generalization via Attribute Selection on Out-of-the-Box Data. Neural Comput. 32(2): 485-514 (2020) - [j95]Yuangang Pan, Ivor W. Tsang, Avinash Kumar Singh, Chin-Teng Lin, Masashi Sugiyama:
Stochastic Multichannel Ranking with Brain Dynamics Preferences. Neural Comput. 32(8): 1499-1530 (2020) - [j94]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Multiview Alignment and Generation in CCA via Consistent Latent Encoding. Neural Comput. 32(10): 1936-1979 (2020) - [j93]Biswajeet Pradhan, Husam Abdulrasool H. Al-Najjar, Maher Ibrahim Sameen, Ivor W. Tsang, Abdullah M. Alamri:
Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks. Remote. Sens. 12(10): 1676 (2020) - [j92]Yanxin Zhang, Yulei Sui, Shirui Pan, Zheng Zheng, Baodi Ning, Ivor W. Tsang, Wanlei Zhou:
Familial Clustering for Weakly-Labeled Android Malware Using Hybrid Representation Learning. IEEE Trans. Inf. Forensics Secur. 15: 3401-3414 (2020) - [j91]Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang:
Secure Metric Learning via Differential Pairwise Privacy. IEEE Trans. Inf. Forensics Secur. 15: 3640-3652 (2020) - [j90]Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - [j89]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Qinfeng Shi, Chengqi Zhang:
Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis, and Case Study. IEEE Trans. Knowl. Data Eng. 32(2): 288-301 (2020) - [j88]Weiwei Liu, Xiaobo Shen, Yew-Soon Ong, Ivor W. Tsang, Chen Gong, Vladimir Pavlovic:
Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2236-2239 (2020) - [j87]Donna Xu, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen:
Survey on Multi-Output Learning. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2409-2429 (2020) - [j86]Jing Chai, Ivor W. Tsang, Weijie Chen:
Large Margin Partial Label Machine. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2594-2608 (2020) - [c113]Yanxin Zhang, Guanping Xiao, Zheng Zheng, Tianqing Zhu, Ivor W. Tsang, Yulei Sui:
An Empirical Study of Code Deobfuscations on Detecting Obfuscated Android Piggybacked Apps. APSEC 2020: 41-50 - [c112]Yang Zhang, Ivor W. Tsang, Yawei Luo, Chang-Hui Hu, Xiaobo Lu, Xin Yu:
Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. CVPR 2020: 7353-7362 - [c111]Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin:
I/O Efficient Approximate Nearest Neighbour Search based on Learned Functions. ICDE 2020: 289-300 - [c110]Yueming Lyu, Ivor W. Tsang:
Curriculum Loss: Robust Learning and Generalization against Label Corruption. ICLR 2020 - [c109]Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama:
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML 2020: 4006-4016 - [c108]Xingrui Yu, Yueming Lyu, Ivor W. Tsang:
Intrinsic Reward Driven Imitation Learning via Generative Model. ICML 2020: 10925-10935 - [c107]Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang:
Graph Cross Networks with Vertex Infomax Pooling. NeurIPS 2020 - [c106]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. NeurIPS 2020 - [i59]Zhuanghua Liu, Ivor W. Tsang:
Towards Sharper First-Order Adversary with Quantized Gradients. CoRR abs/2002.02372 (2020) - [i58]Yang Zhang, Ivor W. Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu:
Face Hallucination with Finishing Touches. CoRR abs/2002.03308 (2020) - [i57]Yang Zhang, Ivor W. Tsang, Yawei Luo, Changhui Hu, Xiaobo Lu, Xin Yu:
Copy and Paste GAN: Face Hallucination from Shaded Thumbnails. CoRR abs/2002.10650 (2020) - [i56]Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang:
Secure Metric Learning via Differential Pairwise Privacy. CoRR abs/2003.13413 (2020) - [i55]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Multi-view Alignment and Generation in CCA via Consistent Latent Encoding. CoRR abs/2005.11716 (2020) - [i54]Xingrui Yu, Yueming Lyu, Ivor W. Tsang:
Intrinsic Reward Driven Imitation Learning via Generative Model. CoRR abs/2006.15061 (2020) - [i53]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan:
Learning Robust Node Representations on Graphs. CoRR abs/2008.11416 (2020) - [i52]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan, Jingchao Su:
Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation. CoRR abs/2009.06884 (2020) - [i51]Hao Zhang, Joey Tianyi Zhou, Tianying Wang, Ivor W. Tsang, Rick Siow Mong Goh:
Deep N-ary Error Correcting Output Codes. CoRR abs/2009.10465 (2020) - [i50]Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang:
Graph Cross Networks with Vertex Infomax Pooling. CoRR abs/2010.01804 (2020) - [i49]Yan Zhang, Ivor W. Tsang, Hongzhi Yin, Guowu Yang, Defu Lian, Jingjing Li:
Deep Pairwise Hashing for Cold-start Recommendation. CoRR abs/2011.00944 (2020) - [i48]Yan Zhang, Ivor W. Tsang, Lixin Duan:
Collaborative Generative Hashing for Marketing and Fast Cold-start Recommendation. CoRR abs/2011.00953 (2020) - [i47]Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya Zhang, Ivor W. Tsang:
Learning on Attribute-Missing Graphs. CoRR abs/2011.01623 (2020) - [i46]Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama:
A Survey of Label-noise Representation Learning: Past, Present and Future. CoRR abs/2011.04406 (2020) - [i45]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. CoRR abs/2011.06446 (2020) - [i44]Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. CoRR abs/2011.11197 (2020)
2010 – 2019
- 2019
- [j85]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang:
A deep learning framework for Hybrid Heterogeneous Transfer Learning. Artif. Intell. 275: 310-328 (2019) - [j84]Donna Xu, Ivor W. Tsang, Eng K. Chew, Cosimo Siclari, Varun Kaul:
A Data-Analytics Approach for Enterprise Resilience. IEEE Intell. Syst. 34(3): 6-18 (2019) - [j83]Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan:
Multi-class Heterogeneous Domain Adaptation. J. Mach. Learn. Res. 20: 57:1-57:31 (2019) - [j82]Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller:
N-ary decomposition for multi-class classification. Mach. Learn. 108(5): 809-830 (2019) - [j81]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: a hint-guided approach for crowdsourcing. Mach. Learn. 108(5): 831-858 (2019) - [j80]Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang:
Metric Learning for Multi-Output Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 408-422 (2019) - [j79]Shudong Huang, Zhao Kang, Ivor W. Tsang, Zenglin Xu:
Auto-weighted multi-view clustering via kernelized graph learning. Pattern Recognit. 88: 174-184 (2019) - [j78]Chao Ma, Ivor W. Tsang, Fumin Shen, Chuancai Liu:
Error Correcting Input and Output Hashing. IEEE Trans. Cybern. 49(3): 781-791 (2019) - [j77]Shaukat R. Abidi, Massimo Piccardi, Ivor W. Tsang, Mary-Anne Williams:
Well-M3N: A Maximum-Margin Approach to Unsupervised Structured Prediction. IEEE Trans. Emerg. Top. Comput. Intell. 3(6): 427-439 (2019) - [j76]Xuanyi Dong, Yan Yan, Mingkui Tan, Yi Yang, Ivor W. Tsang:
Late Fusion via Subspace Search With Consistency Preservation. IEEE Trans. Image Process. 28(1): 518-528 (2019) - [j75]Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Hyperspectral Imagery Classification via Stochastic HHSVMs. IEEE Trans. Image Process. 28(2): 577-588 (2019) - [j74]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning From Noisy Image Labels With Quality Embedding. IEEE Trans. Image Process. 28(4): 1909-1922 (2019) - [j73]Wan-Yu Deng, Amaury Lendasse, Yew-Soon Ong, Ivor Wai-Hung Tsang, Lin Chen, Qing-Hua Zheng:
Domain Adaption via Feature Selection on Explicit Feature Map. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1180-1190 (2019) - [j72]Bo Han, Ivor W. Tsang, Ling Chen, Joey Tianyi Zhou, Celina Ping Yu:
Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 30(12): 3774-3787 (2019) - [c105]Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan:
Label Embedding with Partial Heterogeneous Contexts. AAAI 2019: 4926-4933 - [c104]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jia Wang:
Understanding VAEs in Fisher-Shannon Plane. AAAI 2019: 5917-5924 - [c103]Jiangchao Yao, Hao Wu, Ya Zhang, Ivor W. Tsang, Jun Sun:
Safeguarded Dynamic Label Regression for Noisy Supervision. AAAI 2019: 9103-9110 - [c102]Man Wu, Shirui Pan, Lan Du, Ivor W. Tsang, Xingquan Zhu, Bo Du:
Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. CIKM 2019: 2157-2160 - [c101]Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung:
Marginalized Average Attentional Network for Weakly-Supervised Learning. ICLR (Poster) 2019 - [c100]Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
How does Disagreement Help Generalization against Label Corruption? ICML 2019: 7164-7173 - [c99]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Support Matching: A Novel Regularization to Escape from Mode Collapse in GANs. ICONIP (4) 2019: 40-48 - [c98]Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. IJCAI 2019: 3989-3995 - [c97]Tao Zheng, Wei-Jie Chen, Ivor W. Tsang, Xin Yao:
Rectified Encoder Network for High-Dimensional Imbalanced Learning. PRICAI (2) 2019: 684-697 - [i43]Donna Xu, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen:
A Survey on Multi-output Learning. CoRR abs/1901.00248 (2019) - [i42]Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
How does Disagreement Help Generalization against Label Corruption? CoRR abs/1901.04215 (2019) - [i41]Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. CoRR abs/1905.07933 (2019) - [i40]Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung:
Marginalized Average Attentional Network for Weakly-Supervised Learning. CoRR abs/1905.08586 (2019) - [i39]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Efficient Batch Black-box Optimization with Deterministic Regret Bounds. CoRR abs/1905.10041 (2019) - [i38]Yueming Lyu, Ivor W. Tsang:
Curriculum Loss: Robust Learning and Generalization against Label Corruption. CoRR abs/1905.10045 (2019) - [i37]Yuangang Pan, Weijie Chen, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
Fast and Robust Rank Aggregation against Model Misspecification. CoRR abs/1905.12341 (2019) - [i36]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Probabilistic CCA with Implicit Distributions. CoRR abs/1907.02345 (2019) - [i35]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
Latent Adversarial Defence with Boundary-guided Generation. CoRR abs/1907.07001 (2019) - [i34]Xu Chen, Siheng Chen, Huangjie Zheng, Jiangchao Yao, Kenan Cui, Ya Zhang, Ivor W. Tsang:
Node Attribute Generation on Graphs. CoRR abs/1907.09708 (2019) - [i33]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Improving Generalization via Attribute Selection on Out-of-the-box Data. CoRR abs/1907.11397 (2019) - [i32]Huiting Hong, Xin Li, Yuangang Pan, Ivor W. Tsang:
Domain-adversarial Network Alignment. CoRR abs/1908.05429 (2019) - [i31]Yueming Lyu, Ivor W. Tsang:
Stochastic Implicit Natural Gradient for Black-box Optimization. CoRR abs/1910.04301 (2019) - 2018
- [j71]Bo Han, Yuangang Pan, Ivor W. Tsang:
Robust Plackett-Luce model for k-ary crowdsourced preferences. Mach. Learn. 107(4): 675-702 (2018) - [j70]Yuangang Pan, Bo Han, Ivor W. Tsang:
Stagewise learning for noisy k-ary preferences. Mach. Learn. 107(8-10): 1333-1361 (2018) - [j69]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
'Who Likes What and, Why?' Insights into Modeling Users' Personality Based on Image 'Likes'. IEEE Trans. Affect. Comput. 9(1): 130-143 (2018) - [j68]Donna Xu, Ivor W. Tsang, Ying Zhang:
Online Product Quantization. IEEE Trans. Knowl. Data Eng. 30(11): 2185-2198 (2018) - [j67]Yuguang Yan, Qingyao Wu, Mingkui Tan, Michael K. Ng, Huaqing Min, Ivor W. Tsang:
Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3252-3263 (2018) - [j66]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Multilabel Prediction via Cross-View Search. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4324-4338 (2018) - [j65]Bo Han, Ivor W. Tsang, Ling Chen, Celina Ping Yu, Sai-Fu Fung:
Progressive Stochastic Learning for Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 29(10): 5136-5148 (2018) - [c96]Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Doubly Approximate Nearest Neighbor Classification. AAAI 2018: 3683-3690 - [c95]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Compact Multi-Label Learning. AAAI 2018: 4066-4073 - [c94]Joey Tianyi Zhou, Kai Di, Jiawei Du, Xi Peng, Hao Yang, Sinno Jialin Pan, Ivor W. Tsang, Yong Liu, Zheng Qin, Rick Siow Mong Goh:
SC2Net: Sparse LSTMs for Sparse Coding. AAAI 2018: 4588-4595 - [c93]Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin:
An Efficient Exact Nearest Neighbor Search by Compounded Embedding. DASFAA (1) 2018: 37-54 - [c92]Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang:
Deep Discrete Prototype Multilabel Learning. IJCAI 2018: 2675-2681 - [c91]Chunyang Liu, Ling Chen, Ivor W. Tsang, Hongzhi Yin:
Towards the Learning of Weighted Multi-label Associative Classifiers. IJCNN 2018: 1-7 - [c90]Defu Lian, Kai Zheng, Vincent W. Zheng, Yong Ge, Longbing Cao, Ivor W. Tsang, Xing Xie:
High-order Proximity Preserving Information Network Hashing. KDD 2018: 1744-1753 - [c89]Yan Zhang, Haoyu Wang, Defu Lian, Ivor W. Tsang, Hongzhi Yin, Guowu Yang:
Discrete Ranking-based Matrix Factorization with Self-Paced Learning. KDD 2018: 2758-2767 - [c88]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. NeurIPS 2018: 5841-5851 - [c87]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS 2018: 8536-8546 - [i30]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang:
Degeneration in VAE: in the Light of Fisher Information Loss. CoRR abs/1802.06677 (2018) - [i29]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: A Hint-guided Approach for Crowdsourcing. CoRR abs/1802.09172 (2018) - [i28]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i27]Jiangchao Yao, Ivor W. Tsang, Ya Zhang:
Variational Composite Autoencoders. CoRR abs/1804.04435 (2018) - [i26]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Zero-shot Learning with Complementary Attributes. CoRR abs/1804.06505 (2018) - [i25]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR abs/1804.06872 (2018) - [i24]Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang:
Multi-Context Label Embedding. CoRR abs/1805.01199 (2018) - [i23]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. CoRR abs/1805.08193 (2018) - [i22]Miao Xu, Gang Niu, Bo Han, Ivor W. Tsang, Zhi-Hua Zhou, Masashi Sugiyama:
Matrix Co-completion for Multi-label Classification with Missing Features and Labels. CoRR abs/1805.09156 (2018) - [i21]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang:
Understanding VAEs in Fisher-Shannon Plane. CoRR abs/1807.03723 (2018) - [i20]Bo Han, Gang Niu, Jiangchao Yao, Xingrui Yu, Miao Xu, Ivor W. Tsang, Masashi Sugiyama:
Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. CoRR abs/1809.11008 (2018) - [i19]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-preserving Stochastic Gradual Learning. CoRR abs/1810.00383 (2018) - 2017
- [j64]Weiwei Liu, Ivor W. Tsang:
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. J. Mach. Learn. Res. 18: 81:1-81:36 (2017) - [j63]Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller:
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. J. Mach. Learn. Res. 18: 94:1-94:38 (2017) - [j62]Qi Mao, Li Wang, Ivor W. Tsang:
A unified probabilistic framework for robust manifold learning and embedding. Mach. Learn. 106(5): 627-650 (2017) - [j61]Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun:
Principal Graph and Structure Learning Based on Reversed Graph Embedding. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2227-2241 (2017) - [j60]Jim Jing-Yan Wang, Ivor Wai-Hung Tsang, Xuefeng Cui, Zhiwu Lu, Xin Gao:
Multi-instance dictionary learning via multivariate performance measure optimization. Pattern Recognit. 66: 448-459 (2017) - [j59]Chao Ma, Ivor W. Tsang, Furong Peng, Chuancai Liu:
Partial Hash Update via Hamming Subspace Learning. IEEE Trans. Image Process. 26(4): 1939-1951 (2017) - [j58]Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, Xindong Wu:
Incremental Subgraph Feature Selection for Graph Classification. IEEE Trans. Knowl. Data Eng. 29(1): 128-142 (2017) - [c86]Zhuanghua Liu, Ivor W. Tsang:
Approximate Conditional Gradient Descent on Multi-Class Classification. AAAI 2017: 2301-2307 - [c85]Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun:
Compressed K-Means for Large-Scale Clustering. AAAI 2017: 2527-2533 - [c84]Li Wang, Qi Mao, Ivor W. Tsang:
Latent Smooth Skeleton Embedding. AAAI 2017: 2703-2709 - [c83]Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen:
Compact Multiple-Instance Learning. CIKM 2017: 2007-2010 - [c82]Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jun Sun:
Discovering User Interests from Social Images. MMM (2) 2017: 160-172 - [c81]Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang:
Sparse Embedded k-Means Clustering. NIPS 2017: 3319-3327 - [i18]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning from Noisy Image Labels with Quality Embedding. CoRR abs/1711.00583 (2017) - [i17]Donna Xu, Ivor W. Tsang, Ying Zhang:
Online Product Quantization. CoRR abs/1711.10775 (2017) - 2016
- [j57]Iti Chaturvedi, Yew-Soon Ong, Ivor W. Tsang, Roy E. Welsch, Erik Cambria:
Learning word dependencies in text by means of a deep recurrent belief network. Knowl. Based Syst. 108: 144-154 (2016) - [j56]Xinxing Xu, Wen Li, Dong Xu, Ivor W. Tsang:
Co-Labeling for Multi-View Weakly Labeled Learning. IEEE Trans. Pattern Anal. Mach. Intell. 38(6): 1113-1125 (2016) - [j55]Yiteng Zhai, Yew-Soon Ong, Ivor W. Tsang:
Making Trillion Correlations Feasible in Feature Grouping and Selection. IEEE Trans. Pattern Anal. Mach. Intell. 38(12): 2472-2486 (2016) - [j54]Shenghua Gao, Lixin Duan, Ivor W. Tsang:
DEFEATnet - A Deep Conventional Image Representation for Image Classification. IEEE Trans. Circuits Syst. Video Technol. 26(3): 494-505 (2016) - [j53]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
Understanding Deep Representations Learned in Modeling Users Likes. IEEE Trans. Image Process. 25(8): 3762-3774 (2016) - [c80]Weiwei Liu, Ivor W. Tsang:
Sparse Perceptron Decision Tree for Millions of Dimensions. AAAI 2016: 1881-1887 - [c79]Mingkui Tan, Yan Yan, Li Wang, Anton van den Hengel, Ivor W. Tsang, Qinfeng (Javen) Shi:
Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data. AAAI 2016: 2080-2086 - [c78]Jim Jing-Yan Wang, Ivor Wai-Hung Tsang, Xin Gao:
Optimizing Multivariate Performance Measures from Multi-View Data. AAAI 2016: 2152-2158 - [c77]Yan Yan, Zhongwen Xu, Ivor W. Tsang, Guodong Long, Yi Yang:
Robust Semi-Supervised Learning through Label Aggregation. AAAI 2016: 2244-2250 - [c76]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Shen-Shyang Ho:
Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction. AAAI 2016: 2400-2406 - [c75]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, Chengqi Zhang:
Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. ICDM 2016: 669-678 - [c74]Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh:
Transfer Hashing with Privileged Information. IJCAI 2016: 2414-2420 - [c73]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. ECML/PKDD (1) 2016: 665-680 - [i16]Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller:
N-ary Error Correcting Coding Scheme. CoRR abs/1603.05850 (2016) - [i15]Xinxing Xu, Joey Tianyi Zhou, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh, Yong Liu:
Simple and Efficient Learning using Privileged Information. CoRR abs/1604.01518 (2016) - [i14]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of A Family of Robust Losses for Stochastic Gradient Descent. CoRR abs/1605.01623 (2016) - [i13]Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh:
Transfer Hashing with Privileged Information. CoRR abs/1605.04034 (2016) - 2015
- [j52]Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor W. Tsang:
Memes as building blocks: a case study on evolutionary optimization + transfer learning for routing problems. Memetic Comput. 7(3): 159-180 (2015) - [j51]Liang Feng, Yew-Soon Ong, Meng-Hiot Lim, Ivor W. Tsang:
Memetic Search With Interdomain Learning: A Realization Between CVRP and CARP. IEEE Trans. Evol. Comput. 19(5): 644-658 (2015) - [j50]Marcus Chen, Ivor W. Tsang, Mingkui Tan, Cham Tat Jen:
A Unified Feature Selection Framework for Graph Embedding on High Dimensional Data. IEEE Trans. Knowl. Data Eng. 27(6): 1465-1477 (2015) - [j49]Qi Mao, Ivor W. Tsang, Shenghua Gao, Li Wang:
Generalized Multiple Kernel Learning With Data-Dependent Priors. IEEE Trans. Neural Networks Learn. Syst. 26(6): 1134-1148 (2015) - [j48]Mingkui Tan, Ivor W. Tsang, Li Wang:
Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary. IEEE Trans. Signal Process. 63(3): 727-741 (2015) - [j47]Mingkui Tan, Ivor W. Tsang, Li Wang:
Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals. IEEE Trans. Signal Process. 63(3): 742-753 (2015) - [c72]Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang:
Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. AAAI 2015: 210-216 - [c71]Weiwei Liu, Ivor W. Tsang:
Large Margin Metric Learning for Multi-Label Prediction. AAAI 2015: 2800-2806 - [c70]Haishuai Wang, Peng Zhang, Ivor W. Tsang, Ling Chen, Chengqi Zhang:
Defragging Subgraph Features for Graph Classification. CIKM 2015: 1687-1690 - [c69]Marcus Chen, Santiago Velasco-Forero, Ivor W. Tsang, Tat-Jen Cham:
Objects co-segmentation: Propagated from simpler images. ICASSP 2015: 1682-1686 - [c68]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi:
Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search. IJCAI 2015: 3988-3994 - [c67]Weiwei Liu, Ivor W. Tsang:
On the Optimality of Classifier Chain for Multi-label Classification. NIPS 2015: 712-720 - [i12]Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun:
A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation. CoRR abs/1512.02752 (2015) - 2014
- [j46]Yiteng Zhai, Yew-Soon Ong, Ivor W. Tsang:
The Emerging ?Big Dimensionality? IEEE Comput. Intell. Mag. 9(3): 14-26 (2014) - [j45]Mingkui Tan, Ivor W. Tsang, Li Wang:
Towards ultrahigh dimensional feature selection for big data. J. Mach. Learn. Res. 15(1): 1371-1429 (2014) - [j44]Wen Li, Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 36(6): 1134-1148 (2014) - [j43]Zhixiang Ren, Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Region-Based Saliency Detection and Its Application in Object Recognition. IEEE Trans. Circuits Syst. Video Technol. 24(5): 769-779 (2014) - [j42]Lin Chen, Dong Xu, Ivor Wai-Hung Tsang, Xuelong Li:
Spectral Embedded Hashing for Scalable Image Retrieval. IEEE Trans. Cybern. 44(7): 1180-1190 (2014) - [j41]Shenghua Gao, Ivor Wai-Hung Tsang, Yi Ma:
Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization. IEEE Trans. Image Process. 23(2): 623-634 (2014) - [j40]Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang, Zhixiang Ren:
Concurrent Single-Label Image Classification and Annotation via Efficient Multi-Layer Group Sparse Coding. IEEE Trans. Multim. 16(3): 762-771 (2014) - [c66]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Yan Yan:
Hybrid Heterogeneous Transfer Learning through Deep Learning. AAAI 2014: 2213-2220 - [c65]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
Deep Representations to Model User 'Likes'. ACCV (1) 2014: 3-18 - [c64]Minh Luan Nguyen, Ivor W. Tsang, Kian Ming Adam Chai, Hai Leong Chieu:
Robust Domain Adaptation for Relation Extraction via Clustering Consistency. ACL (1) 2014: 807-817 - [c63]Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan:
Heterogeneous Domain Adaptation for Multiple Classes. AISTATS 2014: 1095-1103 - [c62]Zhongwen Xu, Ivor W. Tsang, Yi Yang, Zhigang Ma, Alexander G. Hauptmann:
Event Detection Using Multi-level Relevance Labels and Multiple Features. CVPR 2014: 97-104 - [c61]Ping Liu, Joey Tianyi Zhou, Ivor Wai-Hung Tsang, Zibo Meng, Shizhong Han, Yan Tong:
Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis. ECCV (4) 2014: 151-166 - [c60]Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan:
Riemannian Pursuit for Big Matrix Recovery. ICML 2014: 1539-1547 - 2013
- [j39]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and scalable weakly labeled SVMs. J. Mach. Learn. Res. 14(1): 2151-2188 (2013) - [j38]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 92-104 (2013) - [j37]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Discovering Low-Rank Shared Concept Space for Adapting Text Mining Models. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1284-1297 (2013) - [j36]Nan Li, Ivor W. Tsang, Zhi-Hua Zhou:
Efficient Optimization of Performance Measures by Classifier Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1370-1382 (2013) - [j35]Qi Mao, Ivor Wai-Hung Tsang:
A Feature Selection Method for Multivariate Performance Measures. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2051-2063 (2013) - [j34]Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang:
Combating Negative Transfer From Predictive Distribution Differences. IEEE Trans. Cybern. 43(4): 1153-1165 (2013) - [j33]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Sparse Representation With Kernels. IEEE Trans. Image Process. 22(2): 423-434 (2013) - [j32]Qi Mao, Ivor Wai-Hung Tsang, Shenghua Gao:
Objective-Guided Image Annotation. IEEE Trans. Image Process. 22(4): 1585-1597 (2013) - [j31]Qi Mao, Ivor Wai-Hung Tsang:
Efficient Multitemplate Learning for Structured Prediction. IEEE Trans. Neural Networks Learn. Syst. 24(2): 248-261 (2013) - [j30]Xinxing Xu, Ivor W. Tsang, Dong Xu:
Soft Margin Multiple Kernel Learning. IEEE Trans. Neural Networks Learn. Syst. 24(5): 749-761 (2013) - [j29]Mingkui Tan, Ivor W. Tsang, Li Wang:
Minimax Sparse Logistic Regression for Very High-Dimensional Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 24(10): 1609-1622 (2013) - [j28]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transfer Ordinal Label Learning. IEEE Trans. Neural Networks Learn. Syst. 24(11): 1863-1876 (2013) - [c59]Zhongwen Xu, Yi Yang, Ivor W. Tsang, Nicu Sebe, Alexander G. Hauptmann:
Feature Weighting via Optimal Thresholding for Video Analysis. ICCV 2013: 3440-3447 - [i11]Mingkui Tan, Ivor W. Tsang, Li Wang:
Is Matching Pursuit Solving Convex Problems? CoRR abs/1302.5010 (2013) - [i10]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and Scalable Weakly Labeled SVMs. CoRR abs/1303.1271 (2013) - 2012
- [j27]Shukai Li, Ivor W. Tsang, Narendra S. Chaudhari:
Relevance vector machine based infinite decision agent ensemble learning for credit risk analysis. Expert Syst. Appl. 39(5): 4947-4953 (2012) - [j26]Lixin Duan, Ivor W. Tsang, Dong Xu:
Domain Transfer Multiple Kernel Learning. IEEE Trans. Pattern Anal. Mach. Intell. 34(3): 465-479 (2012) - [j25]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Visual Event Recognition in Videos by Learning from Web Data. IEEE Trans. Pattern Anal. Mach. Intell. 34(9): 1667-1680 (2012) - [j24]Lin Chen, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement. IEEE Trans. Multim. 14(4): 1057-1067 (2012) - [j23]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang:
Domain Adaptation From Multiple Sources: A Domain-Dependent Regularization Approach. IEEE Trans. Neural Networks Learn. Syst. 23(3): 504-518 (2012) - [j22]Lin Chen, Ivor W. Tsang, Dong Xu:
Laplacian Embedded Regression for Scalable Manifold Regularization. IEEE Trans. Neural Networks Learn. Syst. 23(6): 902-915 (2012) - [j21]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transductive Ordinal Regression. IEEE Trans. Neural Networks Learn. Syst. 23(7): 1074-1086 (2012) - [c58]Mingkui Tan, Ivor W. Tsang, Li Wang, Xinming Zhang:
Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection. AAAI 2012: 1119-1125 - [c57]Lin Chen, Lixin Duan, Ivor W. Tsang, Dong Xu:
Efficient Discriminative Learning of Class Hierarchy for Many Class Prediction. ACCV (1) 2012: 274-288 - [c56]Liang Feng, Yew-Soon Ong, Ivor Wai-Hung Tsang, Ah-Hwee Tan:
An evolutionary search paradigm that learns with past experiences. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c55]Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang, Siwei Jiang:
Pareto Rank Learning in Multi-objective Evolutionary Algorithms. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c54]Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu:
Batch mode Adaptive Multiple Instance Learning for computer vision tasks. CVPR 2012: 2368-2375 - [c53]Jian-Bo Yang, Qi Mao, Qiaoliang Xiang, Ivor Wai-Hung Tsang, Kian Ming Adam Chai, Hai Leong Chieu:
Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach. EMNLP-CoNLL 2012: 744-753 - [c52]Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu:
Co-labeling: A New Multi-view Learning Approach for Ambiguous Problems. ICDM 2012: 419-428 - [c51]Xinxing Xu, Ivor W. Tsang, Dong Xu:
Handling Ambiguity via Input-Output Kernel Learning. ICDM 2012: 725-734 - [c50]Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong, Qi Mao:
Learning Target Predictive Function without Target Labels. ICDM 2012: 1098-1103 - [c49]Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning with Augmented Features for Heterogeneous Domain Adaptation. ICML 2012 - [c48]Qiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao:
A Split-Merge Framework for Comparing Clusterings. ICML 2012 - [c47]Yiteng Zhai, Mingkui Tan, Ivor W. Tsang, Yew-Soon Ong:
Discovering Support and Affiliated Features from Very High Dimensions. ICML 2012 - [c46]Joey Tianyi Zhou, Sinno Jialin Pan, Qi Mao, Ivor W. Tsang:
Multi-view Positive and Unlabeled Learning. ACML 2012: 555-570 - [i9]Jian-Bo Yang, Ivor W. Tsang:
Hierarchical Maximum Margin Learning for Multi-Class Classification. CoRR abs/1202.3770 (2012) - [i8]Qi Mao, Ivor W. Tsang:
Parameter-Free Spectral Kernel Learning. CoRR abs/1203.3495 (2012) - [i7]Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning with Augmented Features for Heterogeneous Domain Adaptation. CoRR abs/1206.4660 (2012) - [i6]Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor Wai-Hung Tsang:
Meme as Building Block for Evolutionary Optimization of Problem Instances. CoRR abs/1207.0702 (2012) - [i5]Mingkui Tan, Ivor W. Tsang, Li Wang:
Towards Large-scale and Ultrahigh Dimensional Feature Selection via Feature Generation. CoRR abs/1209.5260 (2012) - 2011
- [j20]William-Chandra Tjhi, Gary Kee Khoon Lee, Terence Hung, Ivor Wai-Hung Tsang, Yew-Soon Ong, Frédéric Bard, Victor Racine:
Exploratory analysis of cell-based screening data for phenotype identification in drug-siRNA study. Int. J. Comput. Biol. Drug Des. 4(2): 194-215 (2011) - [j19]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
A Family of Simple Non-Parametric Kernel Learning Algorithms. J. Mach. Learn. Res. 12: 1313-1347 (2011) - [j18]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Textual Query of Personal Photos Facilitated by Large-Scale Web Data. IEEE Trans. Pattern Anal. Mach. Intell. 33(5): 1022-1036 (2011) - [j17]Lixin Duan, Wen Li, Ivor Wai-Hung Tsang, Dong Xu:
Improving Web Image Search by Bag-Based Reranking. IEEE Trans. Image Process. 20(11): 3280-3290 (2011) - [j16]Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang:
Domain Adaptation via Transfer Component Analysis. IEEE Trans. Neural Networks 22(2): 199-210 (2011) - [j15]Feiping Nie, Zinan Zeng, Ivor W. Tsang, Dong Xu, Changshui Zhang:
Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering. IEEE Trans. Neural Networks 22(11): 1796-1808 (2011) - [j14]Shutao Li, Mingkui Tan, Ivor W. Tsang, James Tin-Yau Kwok:
A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions. IEEE Trans. Syst. Man Cybern. Part B 41(4): 1003-1014 (2011) - [c45]Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Multi-layer group sparse coding - For concurrent image classification and annotation. CVPR 2011: 2809-2816 - [c44]Wen Li, Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang:
Text-based image retrieval using progressive multi-instance learning. ICCV 2011: 2049-2055 - [c43]Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong:
Healing Sample Selection Bias by Source Classifier Selection. ICDM 2011: 577-586 - [c42]Qi Mao, Ivor Wai-Hung Tsang:
Optimizing Performance Measures for Feature Selection. ICDM 2011: 1170-1175 - [c41]Shukai Li, Ivor W. Tsang, Narendra S. Chaudhari:
Infinite Decision Agent Ensemble Learning System for Credit Risk Analysis. ICMLA (1) 2011: 36-39 - [c40]Shukai Li, Ivor W. Tsang:
Maximum Margin/Volume Outlier Detection. ICTAI 2011: 385-392 - [c39]Jian-Bo Yang, Ivor W. Tsang:
Hierarchical Maximum Margin Learning for Multi-Class Classification. UAI 2011: 753-760 - [c38]Shukai Li, Ivor W. Tsang:
Learning to Locate Relative Outliers. ACML 2011: 47-62 - [c37]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
Two-Layer Multiple Kernel Learning. AISTATS 2011: 909-917 - [i4]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transductive Ordinal Regression. CoRR abs/1102.2808 (2011) - [i3]Qi Mao, Ivor W. Tsang:
Multiple Template Learning for Structured Prediction. CoRR abs/1103.0890 (2011) - [i2]Qi Mao, Ivor W. Tsang:
A Feature Selection Method for Multivariate Performance Measures. CoRR abs/1103.1013 (2011) - 2010
- [j13]Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changshui Zhang:
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction. IEEE Trans. Image Process. 19(7): 1921-1932 (2010) - [j12]Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. Tsang:
Incorporating the loss function into discriminative clustering of structured outputs. IEEE Trans. Neural Networks 21(10): 1564-1575 (2010) - [c36]William-Chandra Tjhi, Gary Kee Khoon Lee, Terence Hung, Yew-Soon Ong, Ivor Wai-Hung Tsang, Victor Racine, Frédéric Bard:
Clustering-based methodology with minimal user supervision for displaying cell-phenotype signatures in image-based screening. BIBM Workshops 2010: 252-257 - [c35]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Visual event recognition in videos by learning from web data. CVPR 2010: 1959-1966 - [c34]Lin Chen, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Tag-based web photo retrieval improved by batch mode re-tagging. CVPR 2010: 3440-3446 - [c33]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia, Peilin Zhao:
Local features are not lonely - Laplacian sparse coding for image classification. CVPR 2010: 3555-3561 - [c32]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Kernel Sparse Representation for Image Classification and Face Recognition. ECCV (4) 2010: 1-14 - [c31]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Location and Scatter Matching for Dataset Shift in Text Mining. ICDM 2010: 773-778 - [c30]Mingkui Tan, Li Wang, Ivor W. Tsang:
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. ICML 2010: 1047-1054 - [c29]Shenghua Gao, Zhengxiang Wang, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Automatic image tagging via category label and web data. ACM Multimedia 2010: 1115-1118 - [c28]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong, Gary Kee Khoon Lee:
Predictive Distribution Matching SVM for Multi-domain Learning. ECML/PKDD (1) 2010: 231-247 - [c27]Qi Mao, Ivor W. Tsang:
Parameter-Free Spectral Kernel Learning. UAI 2010: 350-357 - [i1]Nan Li, Ivor W. Tsang, Zhi-Hua Zhou:
Efficiently Learning Nonlinear Classifiers for Domain Specific Performance Measures. CoRR abs/1012.0930 (2010)
2000 – 2009
- 2009
- [j11]Brian Kan-Wing Mak, Tsz-Chung Lai, Ivor W. Tsang, James Tin-Yau Kwok:
Maximum Penalized Likelihood Kernel Regression for Fast Adaptation. IEEE Trans. Speech Audio Process. 17(7): 1372-1381 (2009) - [j10]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Maximum Margin Clustering Made Practical. IEEE Trans. Neural Networks 20(4): 583-596 (2009) - [c26]Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu, Stephen J. Maybank:
Domain Transfer SVM for video concept detection. CVPR 2009: 1375-1381 - [c25]Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua:
Domain adaptation from multiple sources via auxiliary classifiers. ICML 2009: 289-296 - [c24]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
SimpleNPKL: simple non-parametric kernel learning. ICML 2009: 1273-1280 - [c23]Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang:
Spectral Embedded Clustering. IJCAI 2009: 1181-1186 - [c22]Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang:
Domain Adaptation via Transfer Component Analysis. IJCAI 2009: 1187-1192 - [c21]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Extracting discriminative concepts for domain adaptation in text mining. KDD 2009: 179-188 - [c20]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Using large-scale web data to facilitate textual query based retrieval of consumer photos. ACM Multimedia 2009: 55-64 - [c19]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
T-IRS: textual query based image retrieval system for consumer photos. ACM Multimedia 2009: 983-984 - [c18]Yufeng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou:
A Convex Method for Locating Regions of Interest with Multi-instance Learning. ECML/PKDD (2) 2009: 15-30 - [c17]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. SDM 2009: 341-352 - [c16]Yufeng Li, Ivor W. Tsang, James Tin-Yau Kwok, Zhi-Hua Zhou:
Tighter and Convex Maximum Margin Clustering. AISTATS 2009: 344-351 - 2008
- [j9]Ivor Wai-Hung Tsang, András Kocsor, James Tin-Yau Kwok:
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines. IEEE Trans. Neural Networks 19(4): 610-624 (2008) - [c15]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Improved Nyström low-rank approximation and error analysis. ICML 2008: 1232-1239 - 2007
- [j8]Jooyoung Park, Daesung Kang, Jongho Kim, James T. Kwok, Ivor W. Tsang:
SVDD-Based Pattern Denoising. Neural Comput. 19(7): 1919-1938 (2007) - [j7]James T. Kwok, Ivor Wai-Hung Tsang, Jacek M. Zurada:
A Class of Single-Class Minimax Probability Machines for Novelty Detection. IEEE Trans. Neural Networks 18(3): 778-785 (2007) - [c14]Ivor W. Tsang, András Kocsor, James T. Kwok:
Simpler core vector machines with enclosing balls. ICML 2007: 911-918 - [c13]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Maximum margin clustering made practical. ICML 2007: 1119-1126 - [c12]Ivor W. Tsang, James T. Kwok:
Ensembles of Partially Trained SVMs with Multiplicative Updates. IJCAI 2007: 1089-1094 - 2006
- [j6]Ivor Wai-Hung Tsang, James Tin-Yau Kwok:
Efficient hyperkernel learning using second-order cone programming. IEEE Trans. Neural Networks 17(1): 48-58 (2006) - [j5]Ivor Wai-Hung Tsang, James Tin-Yau Kwok, Jacek M. Zurada:
Generalized Core Vector Machines. IEEE Trans. Neural Networks 17(5): 1126-1140 (2006) - [c11]Ivor W. Tsang, András Kocsor, James T. Kwok:
Diversified SVM Ensembles for Large Data Sets. ECML 2006: 792-800 - [c10]Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey Junfeng Pan:
Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression. ICASSP (1) 2006: 997-1000 - [c9]Ivor W. Tsang, James T. Kwok, Shutao Li:
Learning the Kernel in Mahalanobis One-Class Support Vector Machines. IJCNN 2006: 1169-1175 - [c8]Ivor W. Tsang, András Kocsor, James T. Kwok:
Efficient kernel feature extraction for massive data sets. KDD 2006: 724-729 - [c7]Ivor W. Tsang, James T. Kwok:
Large-Scale Sparsified Manifold Regularization. NIPS 2006: 1401-1408 - 2005
- [j4]Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung:
Core Vector Machines: Fast SVM Training on Very Large Data Sets. J. Mach. Learn. Res. 6: 363-392 (2005) - [c6]Ivor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung:
Very Large SVM Training using Core Vector Machines. AISTATS 2005: 349-356 - [c5]Kin Fung Simon Wong, Ivor W. Tsang, Victor Cheung, S.-H. Gary Chan, James T. Kwok:
Position estimation for wireless sensor networks. GLOBECOM 2005: 5 - [c4]Ivor W. Tsang, James T. Kwok, Kimo T. Lai:
Core Vector Regression for very large regression problems. ICML 2005: 912-919 - 2004
- [j3]James Tin-Yau Kwok, Ivor Wai-Hung Tsang:
The pre-image problem in kernel methods. IEEE Trans. Neural Networks 15(6): 1517-1525 (2004) - [j2]Shutao Li, James Tin-Yau Kwok, Ivor Wai-Hung Tsang, Yaonan Wang:
Fusing images with different focuses using support vector machines. IEEE Trans. Neural Networks 15(6): 1555-1561 (2004) - [c3]Ivor W. Tsang, James T. Kwok:
Efficient Hyperkernel Learning Using Second-Order Cone Programming. ECML 2004: 453-464 - 2003
- [j1]James T. Kwok, Ivor W. Tsang:
Linear dependency between ε and the input noise in ε-support vector regression. IEEE Trans. Neural Networks 14(3): 544-553 (2003) - [c2]James T. Kwok, Ivor W. Tsang:
Learning with Idealized Kernels. ICML 2003: 400-407 - [c1]James T. Kwok, Ivor W. Tsang:
The Pre-Image Problem in Kernel Methods. ICML 2003: 408-415
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-21 01:36 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
